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We discuss how to estimate the interplay between genes (nature) and environments (nurture), with an empirical illustration of the moderating effect of school starting age on one's genetic predisposition towards educational attainment. We argue that gene-environment ( G × E ) studies can be instrumental for (i) assessing treatment effect heterogeneity, (ii) testing theoretical predictions, and (iii) uncovering mechanisms, thereby improving understanding of how (policy) interventions affect population subgroups. Empirically, we find that being old-for-grade and having a higher genetic propensity for education benefits children on assessment tests as they progress through school. In this setting, families appear to increase genetic inequalities while schools seem to reduce them.
The application of chaos theory has positive results in different fields of science. Its nonlinear modeling properties and its vision of dynamic systems have enabled it to capture complex relationships in fields such as physics, financial econometrics, social systems and mathematical demography. This paper reviews the implication of chaos theory in the medical sciences. We carried out a systematic literature review under Cochrane’s international standards. A search strategy was executed with indexed terms (MeSH, DeCS and Emtree) that varied according to each database (Embase, MEDLINE, SciELO, LILACS). The PROSPERO registration number was CRD42023491407. In total, 2598 articles were retrieved, of which 20 were included. Algorithmic applications of chaotic systems were diverse. The medical fields with the largest studies were cardiology, neurology and oncology. The most used software was Matlab, however, in all cases, except one, we did not find open-source codes related to the studies. We found a wide heterogeneity in the studies reviewed, and this was reflected in the scope of research results. While some papers focus on proving the existence of chaotic behavior or understanding the nature of the phenomena being studied, others propose practical implications, such as in prescribing medicines and organizing health units. Not applicable. The online version contains supplementary material available at 10.1186/s42490-026-00111-0.
This study addresses the problem of stock investment strategy, aiming to select the optimal k (k < n) stocks from a set of n stocks within a distributed topology to maximize investment returns. To this end, we propose a dynamic and adaptive neural network model based on the distributed k-winner-take-all (k-WTA) protocol. Firstly, we reformulate the k-WTA problem as a constrained quadratic programming problem and utilize the Sigmoid activation function to relax equality and inequality constraints. Secondly, by combining the simplified constraints with the graph-based topology of stock interactions, we construct a Lagrangian function and develop a time-evolving dynamic neural network whose neuron states update continuously until convergence, reflecting temporal adaptability and convergence dynamics. Unlike traditional centralized methods, the proposed network allows each stock node to communicate only with its connected neighbors, ensuring decentralized computation and scalability. We further present the hardware implementation and theoretically prove the model's stability and convergence under connected graph topologies. Experiments include six static-input tests (different stock counts, parameters, and Gaussian noise) and dynamic validation using real-world stock data from 30 assets over 50 trading days. All seven experimental results confirm the feasibility, effectiveness, and robustness of the proposed model. Comparative analysis with existing WTA models also demonstrates superior adaptability and convergence performance.
Malignant neoplasms of the salivary glands are a heterogeneous group of cancers that include more than 24 malignant histological types in the salivary glands, with different genetic, morphological, and immunohistochemical features and clinical behavior. A retrospective population-based analysis of salivary gland cancers diagnosed between 1994 and 2018 was performed, using data from the Girona and Tarragona cancer registries. Crude incidence rates, European and world-age-standardized incidence rates and incidence trends, measured as the annual percentage change, were estimated. Observed and net survival at 5 and 10 years and 10-y/5-y conditional survival were calculated. The analysis was focused on histological type. A total of 301 cases were recorded in the provinces of Girona and Tarragona during 1994-2018, of which 51.5% were in men and 76.1% in the parotid salivary gland. The most common histology type was the squamous cell carcinoma (17.9%) followed by the mucoepidermoid carcinoma (16.9%). Incidence was 9.2 cases per 1,000,000 person-years for all salivary gland tumors. A decrease in incidence for all cases and in most of the histology types specifically, was observed. For the cohort, the 10-year observed and net survival rates were 37.3 and 55.5%, respectively. Acinar cell carcinoma was the histology with better prognosis at 10 years. A decrease in the overall incidence of cases has been observed, which may be due to better diagnostic or registration accuracy along with changes in exposure to etiological factors such as smoking. Net survival at 10 years was 55.5% for the entire cohort.
In contemporary society, the effective dissemination of medical knowledge and the sustained improvement of health literacy have become paramount priorities for public health. Fortunately, short video platforms have paved new avenues for doctors to teach medical information and communicate health concepts to the public. Despite their substantial significance, short videos still fall short in eliciting viewer engagement, thereby limiting their meaning. In response, this study aims to assist doctors in leveraging teaching styles to refine the design and creation of short videos. Based on data from Douyin (Chinese TikTok), this study employs econometric analyses to examine the influences of two prevalent teaching styles-monologue vs. dialogue-on viewer engagement in short videos, including likes, comments, collections, and shares. Furthermore, our study empirically examines the moderating roles of teaching content characteristics, including knowledge professionalism and knowledge generality, in these influences. The results demonstrate that monologue significantly outperforms dialogue in terms of viewer engagement, spanning from likes to shares. Moreover, the decrease in knowledge professionalism and the increase in knowledge generality can enhance the advantages of monologue over dialogue. This study contributes to the understanding of viewer engagement in short videos and guides doctors to generate high-impact short videos, advancing the public's health self-management and medical knowledge dissemination.
Implantable tibial nerve neuromodulation (ITNM) represents a minimally invasive intervention for urgency urinary incontinence (UUI). This study evaluated the 3-year cost-utility of ITNM with an external wearable battery (Revi System) versus conservative treatments (behavioral ± pharmacotherapy) from a US payer perspective. A cohort state-transition (Markov) model with annual cycles compared ITNM to conservative treatment modalities (behavioral ± pharmacotherapy). ITNM clinical parameters were derived from the OASIS pivotal trial (N = 150); parameter uncertainty was propagated via 20,000 Monte Carlo simulations. Health states captured responder and non-responder status with permitted transitions, rescue interventions (onabotulinumtoxinA, sacral neuromodulation, percutaneous tibial nerve stimulation), and downstream event modules (falls, urinary tract infection, incontinence-associated dermatitis, depression, cognitive decline/dementia, and nursing-home entry). Costs and quality-adjusted life-years (QALYs) were discounted at 3% annually and expressed in 2025 US dollars. Parameter uncertainty was assessed using probabilistic sensitivity analysis (PSA; 20,000 simulations) and tornado analysis. ITNM was both more effective and less costly than behavioral ± pharmacotherapy. Mean 3-year costs were $39,308 versus $43,737 (ΔCost = -$4,428), with mean QALYs of 2.188 and 1.940, respectively (ΔQALY = +0.249). The incremental cost-effectiveness ratio was -$17,818/QALY (dominant). Incremental net monetary benefit at $40,000/QALY was $14,369, with 100% probability of cost-effectiveness across thresholds from $20,000-$150,000/QALY. Key value drivers were responder utility and fall-related parameters. The analysis adopts a US payer perspective with direct medical costs only. Some event risks were applied from population-level sources and may not fully capture patient-level heterogeneity. The 3-year base-case horizon may miss longer-term durability effects, though extended-horizon scenarios support consistent findings. Over 3 years, ITNM with an external wearable battery improves quality-adjusted survival and lowers overall payer costs compared with conservative therapies for UUI, supporting its inclusion as a value-consistent minimally invasive therapy. Urgency urinary incontinence (UUI) is a condition in which people experience sudden, uncontrollable urges to urinate that result in leakage. It affects millions of adults and can lead to falls, skin problems, depression, and nursing home placement. Current treatments include bladder training, pelvic floor exercises, and medications, but most people stop their medications within the first year due to side-effects or limited improvement.Implantable tibial neuromodulation (ITNM) is a newer, minimally invasive option. A small device implanted near the ankle delivers gentle electrical signals, powered by an external wearable battery, to calm the nerves controlling bladder function. A large clinical trial found that about 78% of people treated with ITNM experienced meaningful symptom improvement.Researchers built a computer model to compare the costs and health outcomes of ITNM against conservative treatments over 3 years from the perspective of US health insurers. The model tracked direct treatment costs and costs of related health events such as falls, urinary tract infections, and long-term care.Results showed that ITNM both saved money and improved quality-of-life. Over 3 years, ITNM saved an average of $4,428 per person while providing roughly three additional months of quality-adjusted life. Although ITNM costs more in the first year due to the implant procedure, those costs are offset by fewer complications in the following years. These findings held across a wide range of assumptions, suggesting that ITNM offers good value for people with UUI who have not responded to standard treatments.
Numerous domains, including robotics and artificial intelligence, make extensive use of time-varying quadratic programming (TVQP). Because of the TVQP's importance, a novel adaptive neutrosophic logic/fuzzy neural network TVQP solver, called NZNN-TVQP, is introduced in this work. The proposed TVQP solver uses a recently developed neutrosophic logic/fuzzy adaptive zeroing neural network (NZNN) technique as well as a neutrosophic logic/fuzzy adaptive penalty function. It is important to mention that the NZNN is an advancement on the conventional zeroing neural network (ZNN) technique, which has shown great promise in solving time-varying tasks. To address the TVQP task, the performance of four variations of the NZNN-TVQP solver are examined. All variations of the solver perform remarkably well, as demonstrated by two simulation tests and two real-world applications to portfolio selection problem.
Computerized adaptive tests (CATs) play a crucial role in educational assessment and diagnostic screening in behavioral health. Unlike traditional linear tests that administer a fixed set of pre-assembled items, CATs adaptively tailor the test to an examinee's latent trait level based on their previous responses. We introduce a novel CAT system that builds on recent advances in Bayesian multivariate IRT. Our approach leverages direct sampling from the latent factor posterior distributions, significantly accelerating existing information-theoretic item-selection methods by eliminating the need for computationally intensive Markov chain Monte Carlo simulations. To address the potential suboptimality of one-step-ahead item-selection rules, we also develop a double deep Q-learning algorithm that efficiently learns an optimal item-selection policy offline using a calibrated item bank. Through simulation and real-data studies, we demonstrate that our approach not only accelerates existing item-selection methods but also highlights the potential of reinforcement learning (RL) in CATs. Notably, our Q-learning-based strategy consistently achieves the fastest posterior variance reduction, leading to earlier test termination. These results demonstrate the promise of combining exact posterior sampling with RL to deliver scalable, high-precision CATs.
Developmental plasticity refers to biological adaptations, most often prenatally, to environmental cues. These can help organisms adapt to similar postnatal environments, with health benefits if prenatal and postnatal conditions match. While associations between various prenatal exposures and adverse offspring health have been documented, the interaction between prenatal and postnatal conditions remains less understood. We address this gap by examining whether pre- and postnatal drought exposures interact in their impact on cognitive performance, as early-life nutrition is a critical factor for cognitive development. Standardized math and reading scores from 11-16 year-olds in rural India (N = 2,032,917) from the 2007-2018 Annual Status of Education Report (a cross-sectional cognitive assessment household survey) were combined with University of Delaware Terrestrial Precipitation data. Given the high reliance on rainfed agriculture in the setting, rainfall levels below the 20th percentile of the district-specific long-term mean served as a proxy for nutritional adversities in a quasi-experimental study setup. We show that early-life droughts adversely impact cognitive function. We find positive interaction terms between prenatal and postnatal drought exposures, suggesting that children already exposed to droughts prenatally are better equipped for postnatal droughts. The findings of this study align with the predictions around phenotypic plasticity, i.e., that prenatal conditions prepare organisms for similar postnatal challenges. However, given the increasing unpredictability of the climate, such alignments cannot be planned or anticipated, implying frequent mismatches between prenatal and postnatal conditions. Pregnancy and the first years of life are critical periods for brain development, and adequate nutrition is essential during these times. In many regions, agriculture relies on rainfall, and droughts can cause nutritional shortages. We analyzed math and reading test results of two million children aged 11–16 years in rural India to understand how nutrition before and after birth affects later-life learning. We found that the combination of these two periods matters: droughts in early life generally lead to worse test results, but a drought during pregnancy cushions the effect of a drought a few years later. This is in line with the concept of Predictive Adaptive Responses in humans: biological adaptations to prenatal environmental cues can help prepare for later-life environmental conditions.
Attributing liability in environmental systems involving multiple strategic actors poses significant challenges for policy-makers and regulators, particularly under conditions of uncertainty, feedback dynamics, and distributed responsibility. Traditional deterministic models of causation are often inadequate for such complex contexts. In this study, we propose a novel hybrid framework that integrates AlphaZero-based reinforcement learning with Bayesian probabilistic inference to construct an intelligent decision support system for multi-agent environmental liability attribution. Our primary motivation is to solve the very difficult legal causality puzzles in environmental fields by making a Gestalt leap, offering more legitimate, intelligent and consistent solutions than those currently found in the literature. While this work does not exhaust the full landscape of such puzzles, its principal contribution is to stimulate further inquiry and open new horizons for computational legal reasoning. The framework introduces a Dynamic Causation Index (DCI) that quantifies each agent's simulated contribution to ecological harm and updates their posterior responsibility using Bayesian inference. AlphaZero models the actors' long-term strategic behavior within environmental and regulatory environments, while the Bayesian layer incorporates historical priors and likelihoods derived from simulation outcomes. This enables both counterfactual analysis and probabilistic responsibility estimation, overcoming key limitations in current environmental decision-making practices. We apply this framework to a hypothetical river pollution case study involving three industrial facilities, demonstrating how the model supports transparent, proportionate, and adaptive allocation of liability. The results show that Factory B bears the highest causal share (55.1%), followed by Factory A (37.5%) and Factory C (7.4%), based on their strategic leverage and posterior responsibility estimates. The results illustrate how strategic leverage and probabilistic confidence can be combined to enhance environmental governance and intervention planning. The proposed methodology offers a scalable and explainable approach to regulatory design and system-level environmental accountability, with potential applications across sustainability science, environmental law, and intelligent governance.
In response to the dual challenges of global climate change and China's "dual carbon" goals, the digital economy has become increasingly vital in enhancing urban energy-related carbon emission efficiency. However, traditional studies have not fully considered its interregional network linkages and the resulting spatial spillover effects. To address this gap, this study employs panel data from 271 prefecture-level cities in China between 2011 and 2022 to construct a spatial correlation network of the digital economy. By integrating a modified gravity model, social network analysis, and spatial econometric techniques, we systematically examine the mechanisms, spatial heterogeneity, and spillover effects of this network on urban energy carbon emission efficiency. The findings reveal four main insights: (1) The spatial correlation network of China's urban digital economy demonstrates a complex and multi-threaded structure, with core cities such as Shanghai, Beijing, and Shenzhen dominating digital resource flows. Although overall carbon emission efficiency has improved, disparities across cities have widened. (2) An increase in network centrality significantly enhances energy carbon emission efficiency, with more pronounced positive externalities in the eastern region and in megacities. (3) Network centrality exerts significant spatial spillover effects on efficiency, exhibiting a boundary effect: the spillover coefficient peaks at 170 km and decays with greater distance. (4) Urban innovation capacity serves as a key transmission channel in improving efficiency, whereas industrial upgrading currently imposes certain constraints, as the expansion of energy-intensive industries may inhibit short-term efficiency gains. These results provide practical implications for fostering spatially coordinated carbon reduction and improving urban energy carbon emission efficiency in China.
Bacillus Calmette-Guérin (BCG)-unresponsive high-risk non-muscle-invasive bladder cancer (HR-NMIBC) with carcinoma in situ (CIS) is aggressive and treatment options are suboptimal. TAR-200, a novel intravesical drug-releasing system, received United States (US) Food and Drug Administration (FDA) approval on 09/09/2025 for this population. An economic model compared the cost per responder for US patients with BCG-unresponsive HR-NMIBC with CIS treated with TAR-200 versus other FDA-approved treatments. A 15-month cost-per-responder model was developed from a Medicare payer perspective (2025 USD). Patients treated with TAR-200 monotherapy were compared to those treated with pembrolizumab, nadofaragene firadenovec (NF), nogapendekin alfa inbakicept (NAI)+BCG (with/without reinduction), or valrubicin based on published clinical trial data. Model inputs included costs for initial/subsequent treatment, medical visits, and radical cystectomy (RC). Outcomes comprised the total cost per patient achieving and sustaining complete response (CR) for ≥12 months, based on overall CR rates and digitized Kaplan-Meier curves and swimmer plots for the 12-month duration of response. Patients experiencing non-response received subsequent treatment or underwent an RC. At 15 months, the proportion of patients achieving and sustaining CR for ≥12 months was 43.5% for TAR-200, 18.8% for pembrolizumab, 21.9% for NF, 26.8% for NAI+BCG (36.6% with reinduction), and 10.1% for valrubicin. The total cost per patient achieving and sustaining CR for ≥12 months was $1,892,569 for TAR-200, resulting in cost savings of $698,262 versus pembrolizumab, $406,840 versus NF, $832,346 versus NAI+BCG, and $1,541,999 versus valrubicin. Considering NAI+BCG reinduction, cost savings of $162,599 per patient achieving and sustaining CR for ≥12 months were observed for TAR-200 versus NAI+BCG. Model inputs were based on trial publications, possibly limiting generalizability. TAR-200 demonstrated the highest proportion of patients achieving and sustaining CR for ≥12 months, yielding substantial cost savings per responder compared to other FDA-approved treatments for BCG-unresponsive HR-NMIBC with CIS.
This study evaluated the cost-effectiveness (from the United States [US] societal perspective) of tirzepatide at its maximum-tolerated-dose (MTD) compared to semaglutide (MTD), both administered adjunct to a reduced-calorie diet and increased physical activity. The analysis focused on individuals with obesity (body mass index [BMI] ≥ 30 kg/m2), or overweight (BMI ≥27 to <30 kg/m2 + ≥1 obesity-related complication), using data from the head-to-head Phase-3 SURMOUNT-5 trial (patients without type 2 diabetes [T2D]). This patient-level simulation modeling study assessed the cost and long-term clinical outcomes of tirzepatide (MTD) versus semaglutide (MTD), using data from the SURMOUNT-5 trial population. The modeled population were at risk of developing obesity-related complications including cardiovascular disease (CVD) and obstructive sleep apnea (OSA), amongst others. These outcomes were modeled using cardiometabolic parameters including weight, systolic blood pressure, high-density lipoprotein, glycated hemoglobin (HbA1c) and total cholesterol, by assessing their impact on healthcare and wider societal costs, quality of life, and mortality. Incremental cost-effectiveness ratios (ICERs; cost/quality-adjusted life year [QALY]) and incremental net health benefit (iNHBs) were calculated, and uncertainty was assessed through sensitivity and scenario analyses. Tirzepatide (MTD) was estimated to be less costly and more efficacious compared to semaglutide (MTD) with per patient cost savings of $41,688, 0.506 QALYs gained and positive iNHB of 0.784, indicating a net health benefit for tirzepatide. The model predicted that per 1,000 patients, 70 fewer patients will develop T2D, 10 fewer will develop CVD with tirzepatide (MTD) and patients spend 3.07 more years living with moderate/severe OSA when treated with semaglutide (MTD). Based on this simulation model, using head-to-head SURMOUNT-5 trial data, tirzepatide (MTD) had lower total costs and higher QALYs compared to semaglutide (MTD). This supports that tirzepatide (MTD) is a cost-effective treatment option for individuals with obesity or overweight compared to semaglutide (MTD). This study focused on evaluating the cost-effectiveness of two weight management drugs, tirzepatide and semaglutide, for adults in the US who are overweight or have obesity. Using data from the SURMOUNT-5 trial, the analysis showed that tirzepatide was more effective and less costly, providing better weight loss and health benefits compared to semaglutide.The findings revealed that for every 1,000 individuals treated with tirzepatide, there were 70 fewer cases of type 2 diabetes and 10 fewer cases of heart disease compared to those treated with semaglutide. Additionally, patients on semaglutide experienced a longer duration living with moderate or severe sleep apnea. The study highlighted that tirzepatide led to greater improvements in reducing weight and returning blood sugar levels to normal. Over a lifetime, tirzepatide was found to save $41,688 per patient and provide an additional 0.5 quality-adjusted life years (QALYs; a measure that helps compare how much different treatments improve both length and quality of life), emphasizing its advantages both financially and health-wise.Tirzepatide also demonstrated a reduction in absenteeism (when people are not at work because of illness or health problems) and presenteeism (when people are at work but not fully productive because they are unwell), meaning fewer days lost from work compared to semaglutide, thus highlighting productivity benefits. Overall, the research supports that tirzepatide offered a more cost-effective and beneficial treatment option for weight management in the US healthcare context compared to semaglutide.
The aim of this study was to examine how practitioners currently quantify resistance training (RT), evaluate the perceived effectiveness of popular quantification methods, and identify barriers to quantifying RT load. One hundred and fourteen practitioners (n = 114) who prescribe RT completed an international cross-sectional online survey between November 2023 and April 2024. The survey contained 41 questions, including open-ended, multiple-choice, and Likert-scale items. Descriptive statistics and chi-square tests were used to analyze quantitative data, and thematic analysis was used to analyze qualitative responses. Absolute volume load (82.5%) and session rating of perceived exertion load (77.2%) were the most common, whereas more complex methods like total work (12.3%) and system mass volume load (7.9%) were less commonly used. The most important variables identified by the practitioners were training frequency (75%), working sets (72%), and load (72%). Perceived efficacy of quantification methods was similar across experience groups; however, practitioners' perceptions of maximum dynamic strength volume load was significantly different, with a small to moderate effect. Practitioners with more than 10 years of experience rated relative volume load (75%) and session rating of perceived exertion load (73%) the highest, whereas those with less experience preferred absolute volume load (76%) and session rating of perceived exertion load (76%). The main barriers to RT quantification were measurement/methodological problems (50.5%), athlete-related difficulties (26.3%), and logistical/practical limitations (23.2%). Time constraints (46.7%) were the most common reason against monitoring RT, whereas tracking adaptation/progression (41.1%) and informing periodization/planning (24.7%) were the main reasons for doing so. The methods used to quantify RT load varied widely, with a clear preference for practical approaches. These findings highlight the need for improved education and standardized, practitioner-friendly methods to bridge the research-practice gap.
Prolonged steady-state cycling is characterised by gradual neuromuscular and metabolic acute fatigue, which may affect an athlete’s movement patterns. We hypothesize that athletes might unconsciously reduce cadence as a compensatory strategy to maintain power output. To test this theory, we examined changes in cadence and internal load during extended submaximal cycling. To test this theory, 17 trained cyclists performed a monthly standardised 60-minute effort at 75% of their functional threshold power for five months, yielding 85 paired observations. Cadence behaviour was analysed alongside cardiovascular drift and aerobic decoupling in order to ascertain whether cadence decline reflects a surrogate marker of acute fatigue. The results showed that cadence decline in the second half of the test was significantly correlated with both, cardiovascular drift and aerobic decoupling. Linear mixed model regression analysis revealed a robust association between cadence decline and cardiovascular drift (b = 0.61, p = 0.024), and a repeated measures correlation of r = 0.40 (p < 0.001). On average, each additional rpm of cadence decline corresponded to a 0.61% increase in cardiovascular drift. The correlation between cadence decline and aerobic decoupling was also significant (r = 0.38, p = 0.001) and the regression analysis shows that each additional rpm of cadence decline corresponds to a 0.58% increase in aerobic decoupling (b = 0.58, p = 0.007). These findings suggest that cadence decline is linked to both, cardiovascular and mechanical manifestations of acute fatigue. In practice, cadence monitoring offers a simple, non-invasive and widely accessible method of tracking fatigue. Moreover, it allows the design of training plans incorporating cadence-strategies and providing real-time feedback when cardiovascular strain may impair performance.
Wheat plays a critical role in global food security; however, its vulnerability to rising temperatures introduces significant uncertainty about future yields in a changing climate. Although earlier studies have linked higher temperatures to yield reductions, the moderating influence of terrain elevation on crop-climate interactions remains insufficiently explored. We combine 42 years of county-level yield data (1982-2023) with phenology-specific climate exposures to evaluate how terrain elevation shapes U.S. winter wheat responses to extreme heat and precipitation. Using an econometric framework with county-specific temperature thresholds for extreme degree days, we identify a critical elevation cutoff at 350 meters that delineates two distinct yield-climate regimes. Low-elevation counties exhibit faster long-term yield growth but greater vulnerability to late season heat stress compared to high-elevation counties. Indeed, the late season coincides with the grain-filling stage, which is critical for winter wheat yield outcomes. Rolling-window estimates further reveal that heat-related yield losses have intensified since the 1980s, with late season penalties nearly doubling. Trends also indicate stronger vulnerability among low-elevation counties, especially in the recent period (2004-2023). These findings demonstrate that topography fundamentally mediates climate risks to wheat production. Adaptation may therefore require not only a latitudinal but also an elevational redistribution of wheat cultivation, reshaping the geography of U.S. production under climate change. More broadly, the results underscore the importance of integrating terrain elevation into climate-crop assessments to improve yield projections and inform adaptation strategies across diverse agricultural systems.
Avoidable referral of children for outpatient pediatric general surgical evaluation creates inefficient healthcare utilization and unnecessary social and financial burdens for patients and families. We sought to characterize patient and referring provider characteristics associated with avoidable patient referrals for outpatient pediatric general surgical evaluation in a rural state. This is a multisite retrospective cohort study including patients <18 y referred for outpatient pediatric general surgical evaluation between November 2017 and July 2024. Avoidable referrals were defined as patients who attended pediatric general surgery clinic but did not require an in-clinic procedure, imaging, operation, or clinic follow-up within 1 y. Bivariate analysis and multivariable logistic regression were performed to evaluate for associations between patient and provider factors and avoidable referral. We included 5966 patients. One-quarter of referrals were identified as avoidable (n = 1402, 24%), with children 0-3 y more commonly identified as avoidable (P < 0.001). Umbilical hernia was the most common referral (n = 917); 39% of these were avoidable. Pectus excavatum was most likely to be avoidable (n = 188; 46% avoidable). Referrals for self-pay patients and those placed by emergency medicine providers were more likely to be avoidable [odds ratio 2.5, 95% Confidence Interval (CI) (1.5-4.1) P < 0.001; odds ratio 1.8, 95% CI (1.3-2.7) P < 0.001]. Avoidable referrals had a shorter average time from referral to outpatient pediatric general surgery clinic visit (34 versus 41 d, P < 0.001). Nearly one-quarter of referrals were identified as avoidable. Development of targeted screening prior to outpatient pediatric general surgical evaluation may improve access to pediatric specialty care for indicated referrals and appropriate healthcare utilization.
In the context of increasing global challenges to food security, including climate change, economic disruptions, and supply chain instability, the digital transformation of agricultural circulation systems has attracted growing attention as a potential driver of sustainability and resilience. Using panel data from 30 Chinese provinces spanning 2013-2022, this study empirically examines the impact of digital transformation of circulation (DTC) on the sustainable resilience of food systems (SRFS). A fixed-effects model is employed, complemented by spatial econometric models, mediating effect analysis, and threshold models to capture spatial spillovers, underlying mechanisms, and nonlinear effects. The results indicate that DTC significantly enhances SRFS by optimizing the structure of the food industry, and these findings remain robust after addressing endogeneity and conducting sensitivity analyses. Spatial analysis reveals pronounced heterogeneity in spillover effects: DTC exerts a negative indirect effect on geographically adjacent regions, while generating positive spillovers for regions with strong agricultural trade linkages. Mechanism analysis shows that these effects are driven by the alleviation of factor market distortions and the promotion of industrial convergence. Furthermore, the impact of circulation digitalization on SRFS exhibits diminishing marginal effects and a threshold effect associated with agricultural industrial agglomeration. Taken together, the findings underscore the importance of circulation digitalization in strengthening food system resilience and provide empirical support for the design of more targeted and differentiated digital development strategies in agriculture.
Despite long-standing policy efforts to align population distribution with water availability, the mechanisms linking water resources to population patterns remain poorly understood. Existing studies largely emphasize climatic shocks or assume a positive water-population relationship, leaving the structural drivers of misalignment underexplored. This study addresses this gap by developing an analytical framework that elucidates how water resources influence population distribution through ecological, economic, and environmental paths, grounded in the functional roles of water resources and push-pull theory. Using panel data from 271 prefectures between 2012 and 2021, we assess water-population coordination with Lorenz curve and Gini coefficient and identify causal mechanisms through econometric and path analyses. The results reveal a persistent and counterintuitive negative association between water resource availability and population density, with no evidence of convergence over time. This relationship is driven primarily by ecological and environmental paths, while the economic path is insignificant. Notably, these paths converge in a "dual reduction" mechanism whereby greater water endowment expands green space and reduces wastewater discharge, both contributing to lower population density. These findings challenge the conventional carrying-capacity logic that treats water abundance as a demographic advantage and instead highlight water's role in ecological upgrading and structural transformation. Methodologically, this study advances the literature by integrating a multi-path mechanism framework, while theoretically it reconceptualizes the water-population nexus beyond simple hydrological determinism. The results suggest the need to reassess the "Determining Population on Water" approach and to prioritize ecological and environmental paths, especially green space expansion and wastewater reduction, to improve water-population coordination in water-scarce regions.
Meningitis remains the leading infectious cause of neurological disabilities globally, disproportionately affecting children younger than 5 years and populations in the African meningitis belt. Whereas previous global estimates focused on ten pathogen categories, this study presents the most comprehensive analysis to date, assessing the meningitis burden attributable to 17 causative pathogens based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2023 framework. GBD is a systematic, scientific effort aimed at quantifying the comparative magnitude of health loss caused by diseases, injuries, and risk factors across age groups, sexes, and geographical locations over time. We estimated meningitis mortality using the Cause of Death Ensemble model (CODEm) and morbidity using DisMod-MR 2.1, incorporating data from vital registration, verbal autopsy, surveillance, hospital data, and systematic reviews. Aetiology-specific estimates were generated with pathogen-linked case-fatality ratios and splined binomial regression models. Risk factor attribution was based on established risk-outcome pairs and population attributable fractions. In 2023, there were 259 000 (95% uncertainty interval 202 000-335 000) global deaths and 2·54 million (2·20-2·93) incident cases of meningitis. Children younger than 5 years accounted for more than a third of deaths (86 600 [53 300-149 000]). Streptococcus pneumoniae, Neisseria meningitidis, non-polio enteroviruses, and other viruses were the leading causes of death, while non-polio enteroviruses caused the most cases. The four WHO-defined preventable meningitis pathogens of interest (S pneumoniae, N meningitidis, Haemophilus influenzae, and Group B streptococcus) contributed to 98 700 deaths (77 000-127 000) and 594 000 cases (514 000-686 000). Low birthweight, short gestation, and household air pollution were the top risk factors for meningitis-related mortality. Although mortality and incidence have declined significantly since 1990, progress is insufficient to meet WHO 2030 targets. Despite marked progress in reducing bacterial meningitis via global vaccination campaigns, a substantial meningitis burden persists, attributable both to common pathogens such as S pneumoniae and N meningitidis and to emerging non-bacterial pathogens such as Candida spp and drug-resistant fungi. Achieving WHO goals will require sustained investment in surveillance, vaccination, maternal screening, and health-system strengthening, especially in high-burden settings. Gates Foundation, Wellcome Trust, and UK Department of Health and Social Care.